Ebrahim Omidvar

1.7k total citations · 1 hit paper
31 papers, 1.3k citations indexed

About

Ebrahim Omidvar is a scholar working on Global and Planetary Change, Water Science and Technology and Soil Science. According to data from OpenAlex, Ebrahim Omidvar has authored 31 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Global and Planetary Change, 12 papers in Water Science and Technology and 11 papers in Soil Science. Recurrent topics in Ebrahim Omidvar's work include Flood Risk Assessment and Management (12 papers), Hydrology and Watershed Management Studies (12 papers) and Soil erosion and sediment transport (11 papers). Ebrahim Omidvar is often cited by papers focused on Flood Risk Assessment and Management (12 papers), Hydrology and Watershed Management Studies (12 papers) and Soil erosion and sediment transport (11 papers). Ebrahim Omidvar collaborates with scholars based in Iran, Vietnam and United States. Ebrahim Omidvar's co-authors include Himan Shahabi, Saro Lee, Baharin Bin Ahmad, Ataollah Shirzadi, Binh Thai Pham, John J. Clague, Dieu Tien Bui, Marten Geertsema, Khabat Khosravi and Omid Rahmati and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sustainability and Remote Sensing.

In The Last Decade

Ebrahim Omidvar

31 papers receiving 1.3k citations

Hit Papers

Flood Detection and Susceptibility Mapping Using Sentinel... 2020 2026 2022 2024 2020 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ebrahim Omidvar Iran 16 844 480 387 381 234 31 1.3k
Jagabandhu Roy India 17 808 1.0× 676 1.4× 203 0.5× 342 0.9× 173 0.7× 20 1.2k
Narges Kariminejad Iran 16 694 0.8× 578 1.2× 242 0.6× 321 0.8× 159 0.7× 40 1.3k
Chuluong Choi South Korea 11 619 0.7× 445 0.9× 256 0.7× 253 0.7× 203 0.9× 61 1.2k
Mahdis Amiri Iran 16 663 0.8× 369 0.8× 196 0.5× 311 0.8× 128 0.5× 37 1.0k
Moung-Jin Lee South Korea 21 1.2k 1.4× 756 1.6× 502 1.3× 513 1.3× 305 1.3× 76 1.9k
Chinh Luu Vietnam 17 1.1k 1.3× 436 0.9× 410 1.1× 351 0.9× 285 1.2× 42 1.5k
Sadhan Malik India 18 835 1.0× 293 0.6× 475 1.2× 484 1.3× 138 0.6× 32 1.2k
Mehdi Vafakhah Iran 24 1.0k 1.2× 314 0.7× 899 2.3× 864 2.3× 241 1.0× 112 1.9k
Xia Zhao China 14 447 0.5× 377 0.8× 186 0.5× 235 0.6× 222 0.9× 28 963
Biswajit Das India 21 1.0k 1.2× 325 0.7× 636 1.6× 738 1.9× 154 0.7× 34 1.6k

Countries citing papers authored by Ebrahim Omidvar

Since Specialization
Citations

This map shows the geographic impact of Ebrahim Omidvar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ebrahim Omidvar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ebrahim Omidvar more than expected).

Fields of papers citing papers by Ebrahim Omidvar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ebrahim Omidvar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ebrahim Omidvar. The network helps show where Ebrahim Omidvar may publish in the future.

Co-authorship network of co-authors of Ebrahim Omidvar

This figure shows the co-authorship network connecting the top 25 collaborators of Ebrahim Omidvar. A scholar is included among the top collaborators of Ebrahim Omidvar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ebrahim Omidvar. Ebrahim Omidvar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gholami, Hamid, Yougui Song, Yue Li, et al.. (2024). An explainable integrated machine learning model for mapping soil erosion by wind and water in a catchment with three desiccated lakes. Aeolian Research. 67-69. 100924–100924. 12 indexed citations
5.
Yariyan, Peyman, Mohammadtaghi Avand, Ebrahim Omidvar, et al.. (2021). Optimization of statistical and machine learning hybrid models for groundwater potential mapping. Geocarto International. 37(13). 3877–3911. 51 indexed citations
6.
Shahabi, Himan, Ataollah Shirzadi, Kayvan Ghaderi, et al.. (2020). Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier. Remote Sensing. 12(2). 266–266. 280 indexed citations breakdown →
7.
Nhu, Viet‐Ha, Saeid Janizadeh, Mohammadtaghi Avand, et al.. (2020). GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining Models. Applied Sciences. 10(6). 2039–2039. 87 indexed citations
8.
Panahi, Mahdi, Abolfazl Jaafari, Ataollah Shirzadi, et al.. (2020). Deep learning neural networks for spatially explicit prediction of flash flood probability. Geoscience Frontiers. 12(3). 101076–101076. 104 indexed citations
9.
Bui, Dieu Tien, Ataollah Shirzadi, Himan Shahabi, et al.. (2019). New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed. Forests. 10(9). 743–743. 108 indexed citations
10.
Tuyen, Tran Thi, Ataollah Shirzadi, Binh Thai Pham, et al.. (2019). Development of a Novel Hybrid Intelligence Approach for Landslide Spatial Prediction. Applied Sciences. 9(14). 2824–2824. 57 indexed citations
11.
Pham, Binh Thai, Ataollah Shirzadi, Himan Shahabi, et al.. (2019). Landslide Susceptibility Assessment by Novel Hybrid Machine Learning Algorithms. Sustainability. 11(16). 4386–4386. 156 indexed citations
12.
Bui, Dieu Tien, Himan Shahabi, Ebrahim Omidvar, et al.. (2019). Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm. Remote Sensing. 11(8). 931–931. 99 indexed citations
13.
Pham, Binh Thai, Wei Chen, Hai‐Bang Ly, et al.. (2019). A Novel Intelligence Approach of a Sequential Minimal Optimization-Based Support Vector Machine for Landslide Susceptibility Mapping. Sustainability. 11(22). 6323–6323. 39 indexed citations
14.
Darabi, Hamid, et al.. (2019). Contribution of climatic variability and human activities to stream flow changes in the Haraz River basin, northern Iran. Journal of Hydro-environment Research. 25. 12–24. 60 indexed citations
15.
Omidvar, Ebrahim, et al.. (2019). Performance Evaluation of Artificial Neural Network Models for Downscaling and Predicting of Climate Variables. Journal of watershed management research. 9(18). 80–90. 2 indexed citations
16.
Kavian, Ataollah, et al.. (2016). Prioritizitzation of Haraz sub-watersheds in order to Soil and Water Conservation Practices Based on Morphometric and Land Use Characteristics. Journal of Water and Soil Science. 20(77). 85–99. 3 indexed citations
17.
Kavian, Ataollah, et al.. (2016). Watershed prioritization in order to implement soil and water conservation practices. Environmental Earth Sciences. 75(18). 31 indexed citations
18.
Omidvar, Ebrahim, et al.. (2014). Efficiency of Some Meteorological Drought Indices in Different Time Scales (Case Study: Tajan Basin, Iran). 2(1). 441–453. 9 indexed citations
19.
Solaimani, Karim, et al.. (2012). Landslide Susceptibility Mapping Using Multiple Regression and GIS Tools in Tajan Basin, North of Iran. Environment and Natural Resources Research. 2(3). 16 indexed citations
20.
Solaimani, Karim, et al.. (2008). Investigation of Check Dam`s Effects on Channel Morphology (Case Study: Chehel Cheshme Watershed). Pakistan Journal of Biological Sciences. 11(17). 2083–2091. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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